PUBG_Finish_Placements_Prediction-Exploratory-Data-Analysis-

Working on the Exploratory Data Analysis according to the different aspects like Killers,Runners,Drivers,Swimmers,Healers and Feature Enginering.

Getting Started

• First Download the Dataset from the link given in the Data Sources.
• Clone the repo
• Go to the File and run the .py file through cmd with python3 as the default version
• See the different plots and the predictions regarding the datasets.
• Enjoy the better experience of how you can increase the chances to win the Chicken Dinner in the PUBG.

Technologies:

• Programming Language: Python
• Libraries: Pandas, Scikit-learn, Matplotlib, Seaborn
• Visualization: plotly

Data Sources:

Datasets used for the analysis can be found on the given link.

Prerequisites

What things you need to install the software and how to install them

pip install python3

Installing

Install all the dependencies through the python3 and also on the Visual Studio Code.

Say what the step will be

pip install vscode && pip install python3

And also

install matplotlib,seaborn,numpy,sklearn through python3

Built With

• VisualStudio Code - Best Editor for the Code Writing and Debugging
• Python - All the dependecy are used on Python3
• Kaggle For PUBG Dataset - Website to practice the Machine Learning

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

Versioning

We use SemVer for versioning. For the versions available, see the tags on this repository.

Authors

• Rahul Chandra - Initial work - Machine Learning Enthusiast

License

This project is licensed under the MIT License - see the LICENSE.md file for details

Acknowledgments

• Works on only with the Python3 dependencies(so please take care of it)
• Practiced how to work on the Exploratory Data Analysis Techniques)